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demonstrated ability to work within a geographically distributed networks of collaboration Proven experience in developing and implementing machine learning models and algorithms, ideally in the healthcare
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movement; (iii) generate benefits for both society and the environment by guiding possible mitigation strategies; and (iv) drive technological progress through the development of novel algorithms
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analysed by bespoke machine-learning driven algorithms, combined with physical models, to de-noise images, identify features and correlate properties, giving critical insights into power loss pathways
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algorithms, ideally in the healthcare or mental health domain Desirable criteria Track record of successful research grant applications, or attempts to obtain grant funding. Previous development of ML-based
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About Us We are seeking experts in medical image deep learning to join our team and help develop novel computationally efficient segmentation algorithms. We welcome application from individual with
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populations. Knowledge of real-time control algorithms for assistive or rehabilitation systems. Experience contributing to patent applications, translational research, or spin-out formation. Downloading a copy
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this, the Fellow will implement a universal design methodology for such fluids of complex rheology, using a Machine Learning (ML) algorithm to be incorporated in a Computational Fluid Dynamics framework. Training
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. Experience conducting or supporting user studies involving patients or vulnerable populations. 4. Knowledge of real-time control algorithms for assistive or rehabilitation systems. 5. Experience
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modelling, advanced AI algorithms, and decision-support tool development for various hydrogen technologies-based energy systems. Responsibilities will include programming, analysing and interpreting data, and
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computational frameworks that combine 4D point cloud data, geospatial analysis, and advanced ML/DL algorithms. Integrate dynamic environmental datasets into immersive and interactive prototypes for scenario